Summary

Snowshoe Hare, Lepus americanus, is a species of hare found in North America, primarily in the northern boreal forests. It is a keystone prey species and can experience fluctions in population density. This analysis explores these fluctuations in a population of snowshoe hares in the Bonanza Creek Experimental Forest from 1999 to 2012. Data was collected by Kielland et al. from 1999 to 2012.

Citation:
Kielland K., F. S. Chapin, R. W. Ruess. 2017. Snowshoe hare physical data in Bonanza Creek Experimental Forest: 1999-Present. Environmental Data Initiative. https://doi.org/10.6073/pasta/03dce4856d79b91557d8e6ce2cbcdc14.


1. Plot snowshoe hare abundance between 1999-2012, group by sex

##### Wrangle the data to inclue variables of choice: sex and weight of snowshoe hares#####


### Total observations = 3380 (including all sex and NA values)
### Observations with KNOWN sex = 2628 (includes M, F, m, f)



#### Clean up DATE and extract YEAR

snowshoe$date = as.Date(snowshoe$date, "%m/%d/%y")

snowshoe$year = as.numeric(format(snowshoe$date, "%Y"))


## Get total abundance for snowshoe hare observations by counting up total observations by year
## Filtered out observations where the sex was unknown ******

# Get counts by year/sex
abundance <- snowshoe %>% 
  select(year, sex, weight) %>% 
    mutate(sex = case_when(sex =="M" ~ "Male",
                         sex == "F" ~ "Female",
                         sex == "f" ~ "Female",
                         sex == "m" ~ "Male"
                         )) %>% 
  group_by(year, sex) %>% 
  drop_na() %>% 
  tally() 

# Total observations for male/female with weights
abundance_weights <- snowshoe %>% 
  select(year, sex, weight) %>% 
    mutate(sex = case_when(sex =="M" ~ "Male",
                         sex == "F" ~ "Female",
                         sex == "f" ~ "Female",
                         sex == "m" ~ "Male"
                         )) %>%  
  drop_na()  

# Plot Total Abundance 
abundance_plotly <- ggplot(abundance, aes(x = year, y = n)) + 
  geom_line(aes(color = sex, text = n)) + 
  ggtitle("Population Density of Snowshoe Hares in the \n Bonanza Creek Experimental Forest, 1999-2012") +
  theme_classic() +
  xlab("Year") +
  ylab("Number of Snowshoe Hares Recorded") + 
  theme(plot.title=element_text(hjust=0.5)) +
  labs(color = "Sex")
## Warning: Ignoring unknown aesthetics: text
abundance_plotly <- ggplotly(abundance_plotly)
abundance_plotly


Figure 1. Population Density of Snowshoe Hares, 1999-2012. Capture and re-capture studies were conducted on a snowshoe hare population in Bonanza Creek Experimental forest between 1999 and 2012. Data was collected on the sex, weight, and highfeet length. This graph only shows data for snowshoe hares where the sex was confirmed. Total observations during the study period were n = 3380. Observations including hares with known sex is n = 2628.

There is a significant increase in abundance between 1998 and 1999 for both males and females, and then a subsequent decrease between 1999 and 2002. Between 2002 and 2009, both male and female snowshoe hares again increase in abundance and then drop off again between 2009 and 2012. Some of the driving factors for these fluctuations could be predation or changes in habitat, such as vegetation cover.


### Create summary table for abundance 
# total observations for male and female by year 


abundance_table <- kable(abundance,
                         col.names = c("Year", "Sex", "Count")) %>% 
  kable_styling(bootstrap_options = c("striped", "hover"), 
                full_width = F, 
                position = "float_right",
                fixed_thead = T
                ) %>% 
  scroll_box(width = "200px", height = "300px")



abundance_table
Year Sex Count
1998 Female 15
1998 Male 18
1999 Female 163
1999 Male 185
2000 Female 121
2000 Male 107
2001 Female 38
2001 Male 57
2002 Female 11
2002 Male 17
2003 Female 34
2003 Male 23
2004 Female 45
2004 Male 29
2005 Female 103
2005 Male 58
2006 Female 78
2006 Male 33
2007 Female 132
2007 Male 58
2008 Female 164
2008 Male 133
2009 Female 247
2009 Male 185
2010 Female 207
2010 Male 113
2011 Female 129
2011 Male 80
2012 Female 24
2012 Male 21

Table 1. Abundance by year and sex. Population counts by year and sex. This dataset only shows observations for hares where sex was known.




2. Compare weights between male and female snowshoe hares

hare_weights <- ggplot(abundance_weights, aes(x = year, y = weight)) +
  geom_point(aes(color = sex)) +
  xlab("Year") +
  ylab("Weight (g)") +
  facet_wrap(~sex) +
  labs(color = "Sex") +
  theme_bw()
  

hare_weights

Figure 2. Snowshoe Hare weights for Males and Females. Range of weights for male and females during study period between 1999 and 2012.

# Calculate mean weight per year for males and females 

avg_weight <- abundance_weights %>% 
  group_by(year, sex) %>% 
  summarize(
    mean_weight = round(mean(weight), digits = 1),
    sample = length(sex)
  )




# Separate Male and Female into separate dataframes 

mean_weight_female <- avg_weight %>% 
  filter(sex == "Female") %>% 
  select(year, mean_weight, sample) %>% 
  rename("Year" = year, "Mean Weight (g)" = mean_weight, "Count" = sample)

mean_weight_male <- avg_weight %>% 
  filter(sex == "Male") %>% 
  select(year, mean_weight, sample) %>% 
  rename("Year" = year, "Mean Weight (g)" = mean_weight, "Count" = sample)

# Merge male and female back together

weight_by_sex <- merge(mean_weight_female, mean_weight_male, by = "Year")

  
  

# Create kable table for mean weights

weights_table <-kable(weight_by_sex,
                      col.names = c("Year", "Mean Weight (g)", "Count", "Mean Weight (g)", "Count")) %>% 
  add_header_above(c(" " = 1, "Female" = 2, "Male" = 2)) %>% 
   kable_styling(bootstrap_options = c("striped", "hover"), 
                full_width = F, 
                position = "left",
                fixed_thead = T
                ) 
weights_table
Female
Male
Year Mean Weight (g) Count Mean Weight (g) Count
1998 1735.3 15 1646.7 18
1999 1295.4 163 1239.1 185
2000 1444.3 121 1300.5 107
2001 1437.8 38 1358.5 57
2002 1047.7 11 1301.5 17
2003 1205.4 34 1223.5 23
2004 1536.4 45 1372.4 29
2005 1232.3 103 1363.4 58
2006 1361.3 78 1486.4 33
2007 1426.9 132 1294.1 58
2008 1366.0 164 1395.9 133
2009 1352.2 247 1330.3 185
2010 1381.9 207 1428.1 113
2011 1380.2 129 1475.8 80
2012 1291.2 24 1331.0 21


Table 2. Mean Weight for Male and Female Snowshoe Hares (1999-2012). Mean weight for male and female hares for each year of the study period and count for each year. The highest mean weight for both males and females was during 1998.